IntermediateMarket Research & Product Selection AI

Review and Pain-Point Mining | Comparative Decision Prompt

Review and Pain-Point Mining | Comparative Decision Prompt is a copyable AI prompt for ecommerce sellers. Use it to compare candidate options against one consistent decision framework. Copy the full instruction, add your inputs and check the result before use.

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Platform agnostic
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chatgpt · claude · gemini
Prompt Template
01

How the Review and Pain-Point Mining | Comparative Decision Prompt works

Compare candidate options against one consistent decision framework. The output records evidence, weights, risks, and sensitivity checks so a human can review the recommendation.

02

Key instructions and output

The points below describe the task and expected output in this prompt.

01

Expected output

The deliverable should include Themes and frequency, Positive and negative drivers, Pain-point severity, Product and content recommendations, and Representative customer quotes.

03

Parameter guide

Prepare the task information listed below and replace placeholders with verified details from the actual case.

[Option A]

Replace this placeholder with verified, task-specific information before running the prompt.

[Option B]

Replace this placeholder with verified, task-specific information before running the prompt.

[Option C]

Replace this placeholder with verified, task-specific information before running the prompt.

[Review text]

Replace this placeholder with verified, task-specific information before running the prompt.

[Star rating]

Replace this placeholder with verified, task-specific information before running the prompt.

[SKU or competitor]

Replace this placeholder with verified, task-specific information before running the prompt.

[Date]

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[Verified-purchase status]

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04

Copy the complete prompt

The complete source is shown below. Copy it from the top right to use it.

You are an ecommerce review research analyst. Compare [Option A], [Option B], and [Option C] for the objective: analyze large volumes of reviews for themes, sentiment, usage occasions, and unmet needs. Inputs: [Review text], [Star rating], [SKU or competitor], [Date], [Verified-purchase status]. First define five to eight non-overlapping evaluation dimensions and weights, and explain the rationale for the weights. Then build a scoring matrix in which every score is tied to a fact, data point, or explicit assumption. Provide the best choice, conditions under which it is best, irreversible risks, the lowest-cost validation method, and Themes and frequency, Positive and negative drivers, Pain-point severity, Product and content recommendations, Representative customer quotes. Do not invent missing information to force a conclusion. Special requirement: Preserve the specific meaning of reviews. Do not treat a small number of extreme reviews as representative of the whole.
05

Test this prompt on a real task

Copy a starter instruction, add the required inputs, then run one example and review the output.

01

Review and Pain-Point Mining | Comparative Decision Prompt

The deliverable should include Themes and frequency, Positive and negative drivers, Pain-point severity, Product and content recommendations, and Representative customer quotes. Compare options and make a reviewable review and pain-point mining decision

Show prompt and variablesHide prompt and variables
You are an ecommerce review research analyst. Compare [Option A], [Option B], and [Option C] for the objective: analyze large volumes of reviews for themes, sentiment, usage occasions, and unmet needs. Inputs: [Review text], [Star rating], [SKU or competitor], [Date], [Verified-purchase status]. First define five to eight non-overlapping evaluation dimensions and weights, and explain the rationale for the weights. Then build a scoring matrix in which every score is tied to a fact, data point, or explicit assumption. Provide the best choice, conditions under which it is best, irreversible risks, the lowest-cost validation method, and Themes and frequency, Positive and negative drivers, Pain-point severity, Product and content recommendations, Representative customer quotes. Do not invent missing information to force a conclusion. Special requirement: Preserve the specific meaning of reviews. Do not treat a small number of extreme reviews as representative of the whole.

Inputs to replace in this prompt

[Option A]
Replace this placeholder with verified, task-specific information before running the prompt.
[Option B]
Replace this placeholder with verified, task-specific information before running the prompt.
[Option C]
Replace this placeholder with verified, task-specific information before running the prompt.
[Review text]
Replace this placeholder with verified, task-specific information before running the prompt.
[Star rating]
Replace this placeholder with verified, task-specific information before running the prompt.
[SKU or competitor]
Replace this placeholder with verified, task-specific information before running the prompt.
[Date]
Replace this placeholder with verified, task-specific information before running the prompt.
[Verified-purchase status]
Replace this placeholder with verified, task-specific information before running the prompt.
06

What to check before using the output

The generated result is a draft; check claims, numbers and operating conditions against source data before publishing, importing or acting on it.

Operating note 1

Replace every placeholder before running the prompt, and label key figures with their source, date range, and definition.

Operating note 2

Preserve the specific meaning of reviews. Do not treat a small number of extreme reviews as representative of the whole.

Operating note 3

Before uploading order, customer, contract, or supplier data, redact sensitive information and comply with platform terms, privacy policies, NDAs, and company data-governance requirements. Have the responsible operator review the result before it is published, sent, or executed.

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Source & attribution

Compilation note and reference material

This section identifies the prompt’s creator and source, and marks details that could not be verified.

Compiled by

Vendolune

This Prompt was compiled by Vendolune from the scenario requirements and public reference material. The reference-page author is not credited as this Prompt's author.

Reference materialHelium 10

This link is reference material and does not establish its page author as the author of this Prompt. The author provides a prompt-driven process from keyword research through titles, bullets, descriptions, backend search terms, and ongoing optimization, while requiring real keyword and product data.

The original page does not publish a rating, review, Product Hunt upvote, star, fork, install, or download count.

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